Rare event detection using error-corrected DNA and RNA sequencing

Wing H. Wong, R. Spencer Tong, Andrew L. Young, Todd E. Druley

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Conventional next-generation sequencing techniques (NGS) have allowed for immense genomic characterization for over a decade. Specifically, NGS has been used to analyze the spectrum of clonal mutations in malignancy. Though far more efficient than traditional Sanger methods, NGS struggles with identifying rare clonal and subclonal mutations due to its high error rate of ~0.5–2.0%. Thus, standard NGS has a limit of detection for mutations that are >0.02 variant allele fraction (VAF). While the clinical significance for mutations this rare in patients without known disease remains unclear, patients treated for leukemia have significantly improved outcomes when residual disease is <0.0001 by flow cytometry. In order to mitigate this artefactual background of NGS, numerous methods have been developed. Here we describe a method for Error-corrected DNA and RNA Sequencing (ECS), which involves tagging individual molecules with both a 16 bp random index for error-correction and an 8 bp patient-specific index for multiplexing. Our method can detect and track clonal mutations at variant allele fractions (VAFs) two orders of magnitude lower than the detection limit of NGS and as rare as 0.0001 VAF.

Original languageEnglish
Article numbere57509
JournalJournal of Visualized Experiments
Volume2018
Issue number138
DOIs
StatePublished - Aug 3 2018

Keywords

  • Bioinformatics
  • Early detection
  • Error-corrected sequencing
  • Genetics
  • Genomics
  • Issue 138
  • Molecular tagging
  • Rare event detection

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